Determining the Impact of Key Social Determinants on Mental Wellbeing of Aboriginal Peoples in Canada
Bibliographic record
Abstract
Mental health ailments are on the rise across the world. Across Canada, it is believed that one out of every fifth person experiences some form of mental healthcare issue. The present study builds on the Aboriginal Peoples Survey (APS) 2017 to determine the impact of socioeconomic and demographic factors including age, gender, household income, mental health condition (anxiety disorder), highest level of education, housing conditions, and total 2016 personal income on the self-perceived mental health status of Aboriginal peoples. Statistical analysis was conducted using SPSS. Data analysis was carried out using multinomial regression analysis and descriptive statistics. Results collected from statistical analysis revealed that income (total income level in a year and household income to meet basic needs) plays a significant role in how Aboriginal peoples perceive their current mental health status. Satisfaction levels with housing conditions and pre-existing mental health conditions also influence the mental health and well-being of the indigenous people. The linkage between income and mental health could be used to develop future well-being policies for Aboriginal peoples that focus on providing better income and earning opportunities to these people.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".